Point Cloud Reconstruction and Denoising.
We convert depth maps to point clouds and transform them into a world coordinate system with camera extrinsic parameters. However, the depth images captured by Kinect contain noisy pixels, which are prominent at subject boundaries where the depth gradient is large. To solve this issue, we first generate a binary boundary mask through edge finding with Laplacian of Gaussian Filters. Since our cameras have highly overlapped views to supplement points for one another, we apply a more aggressive threshold to remove boundary pixels. After the point cloud is reconstructed from the denoised depth images, we apply Statistical Outlier Removal  [1]} to further remove sprinkle noises.
